The current IoT landscape is highly OEM-centric – it is heavily OEM-data-biased and at first services the interests of the equipment manufacturer. The end customers, the asset operators, plant owners, and process owners, have been sharing their operational data with their OEM equipment suppliers in return for insights into asset conditions and improved maintenance. And depending on the strategies deployed by the OEM, the end customers and operators often have valid concerns about the credibility of these insights delivered by the OEMs. And more often than not, it is impossible to get a true understanding of the approaches that led to the insights. (Take the over-simplified example of auto-manufacturer-recommended oil change every 3,000 miles.)
However, the end customers are increasingly demanding improved equipment and process reliability across their whole asset/equipment estate. This estate includes operational assets from multiple OEM providers across the entire set of manufacturing and medical laboratory processes, across multiple geographies, with multiple technologies and wide variations in equipment age. And every organization needs a systematic and coordinated set of activities and practices which sustainably manages all its assets’ performance, risks and expenditures over their life cycles for the purpose of achieving the organizational strategic plan.
Given these conditions, reliance on OEM recommendations not only leads to fragmented asset management strategies across the estate, but these recommendations have mostly proven to be the least effective for assets with medium to high criticality.
End customers and asset operators require clear and accurate recommendations on process optimization. Unfortunately, many consider this information to be their proprietary data, their playbook, their operational cookbook, and this is confidential to their ecosystem. In addition, many manufacturing or process operations are competitive and thus deferential to their product offering and cost.
There is a trend in which end-customer business models move to a lower-cost model, with the lower deployed operational resource. However, employed process technology generally is increasing in complexity.
Makoro™, therefore, recommends and delivers continuous improvement in quality and asset/equipment total through-life cost while maintaining high process availability (OEE) and delivering a reduction in downtime based on the end customers proprietary data from their whole ecosystem while still sharing nominated data with selected OEM providers.
Makoro™ is a technology for the end-user, the asset operator.
Makoro™, by design, works with multiple and simultaneous data sources, protocols and connected and non-connected devices, legacy operational, and maintenance data. You do not have to have IoT fully deployed with every edge device reporting to get immediate value.
We sell directly to the asset operators, through process consultants and also to OEMs that recognize any IoT platform must support all the process stakeholders while protecting the intellectual proprietary of the end customer process.
We also licence our technology via API to extend the capability offering of already deployed Enterprise Asset Management (EAM), Field Service Management (FSM), Asset Performance Management (APM), Computerized Maintenance Management (CMMS) and Enterprise Resource Planning (ERP) systems.
Too many people tell you where the problem is, but shy away from recommending solutions. This is where Makoro™shines – we not only pinpoint the problem but also recommend solutions.
Makoro™ lets you take control of the proprietary data you collect from your line and your manufacturing process devices. You decide what you wish to share with the OEMs providing your equipment maintenance.
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